Using Passive Cavitation Images to Classify High-Intensity Focused Ultrasound Lesions

Abstract

Passive cavitation imaging provides spatially resolved monitoring of cavitation emissions. However the diffraction limit of a linear imaging array results in relatively poor range resolution. Poor range resolution has limited prior analyses of the spatial specificity and sensitivity of passive cavitation imaging for predicting thermal lesion formation. In this study, this limitation is overcome by orienting a linear array orthogonal to the HIFU propagation direction and performing passive imaging. Fourteen lesions were formed in ex vivo bovine liver samples as a result of 1.1 MHz continuous-wave ultrasound exposure. The lesions were classified as focal, “tadpole”, or pre-focal based on their shape and location. Passive cavitation images were beam-formed from emissions at the fundamental, harmonic, ultraharmonic, and inharmonic frequencies with an established algorithm. Using the area under a receiver operator characteristic curve (AUROC), fundamental, harmonic, and ultraharmonic emissions were shown to be significant predictors of lesion formation for all lesion types. For both harmonic and ultraharmonic emissions, pre-focal lesions were classified most successfully (AUROC values of 0.87 and 0.88, respectively), followed by tadpole lesions (AUROC values of 0.77 and 0.64, respectively), and focal lesions (AUROC values of 0.65 and 0.60, respectively).

Enhancement of High-Intensity Focused Ultrasound Heating by Short-Pulse Generated Cavitation

“…Cavitation-enhanced heating by a trigger HIFU sequence can generate a coagulation region with high efficiency and reproducibility without distortion of coagulation region such as to a tadpole shape [12,22,24]. Good agreement between the ultrasonic cavitation image and coagulation area Coagulation (lateral) Coagulation (axial) Cavitation cloud (axial) Figure 13.…”

“…Cavitation-enhanced heating by a trigger HIFU sequence can generate a coagulation region with high efficiency and reproducibility without distortion of coagulation region such as to a tadpole shape [12,22,24]. Good agreement between the ultrasonic cavitation image and coagulation area indicates possibility to accurately estimate coagulation area in real time from ultrasound images, though a coagulation detection method such as decorrelation imaging [72] is also required to determine the appropriate acoustic dose.…”

“…The volumetric oscillation of bubbles increases ultrasonic energy dissipation in the vicinity of the bubbles through three mechanisms such as acoustic radiation, thermal, and viscous damping, which resulted in the enhanced heating effect. The effect of bubble-enhanced ultrasonic heating has been investigated experimentally [11][12][13][14][15][16][17][18][19][20][21][22][23][24] and numerically [25,26]. Although increased heat depositions were obtained using microbubbles in the previous research, distorted coagulation regions or temperature distribution were observed, such as tad-pole shaped [12,22,24] or pre-focal [13,19,[24][25][26] heating regions.…”

“…The effect of bubble-enhanced ultrasonic heating has been investigated experimentally [11][12][13][14][15][16][17][18][19][20][21][22][23][24] and numerically [25,26]. Although increased heat depositions were obtained using microbubbles in the previous research, distorted coagulation regions or temperature distribution were observed, such as tad-pole shaped [12,22,24] or pre-focal [13,19,[24][25][26] heating regions. A "trigger 2 of 20 HIFU" sequence that consists of high-intensity short pulses and following moderate-intensity long bursts has been investigated to avoid such distorted coagulation regions while enhancing the ultrasonic heating [27][28][29][30][31][32][33][34][35][36].…”

Quantitative Frequency-Domain Passive Cavitation Imaging

“…Passive cavitation imaging has been used to study high-intensity focused ultrasound thermal ablation [30], [33]–[37], ultrasound-mediated delivery of drugs, drug substitutes, and therapeutic biologics [38]–[42], histotripsy [43], and cavitation dynamics [41], [44]–[50]. The imaging algorithm has also been modified to account for aberration [51]–[54] and to improve the image resolution [40], [55], [56].…”